A Prediction Model of the Incidence of Type 2 Diabetes in Individuals with Abdominal Obesity: Insights from the General Population

Overview

Journal Diabetes Metab Syndr Obes

Publisher Dove Medical Press

Specialty Endocrinology

Date 2022 Nov 22

PMID 36411787

Authors

Caixia Tan

Bo Li

Lingzhi Xiao

Yun Zhang

Yingjie Su

Ning Ding

Affiliations

Soon will be listed here.

Abstract

Background: This study aimed to distinguish the risk factors for type 2 diabetes mellitus (T2DM) and construct a predictive model of T2DM in Japanese adults with abdominal obesity.

Methods: This study was a post hoc analysis. A total of 2012 individuals with abdominal obesity were included and randomly divided into training and validation groups at 70% (n = 1518) and 30% (n = 494), respectively. The LASSO method was used to screen for risk variables for T2DM, and to construct a nomogram incorporating the selected risk factors in the training group. We used the C-index, calibration plot, decision curve analysis, and cumulative hazard analysis to test the discrimination, calibration and clinical significance of the nomogram.

Results: In the training cohort, the C-index and receiver operating characteristic were 0.819 and the 95% CI was 0.776-0.858, with a specificity and sensitivity of 77% and 74.68%, respectively. In the validation cohort, the C-index was 0.853; sensitivity and specificity were 77.6% and 88.1%, respectively. The decision curve analysis showed that the model's prediction was effective and cumulative hazard analysis demonstrated that the high-risk score group was more likely to develop T2DM than the low-risk score group.

Conclusion: This nomogram may help clinicians screen abdominal obesity at a high risk for T2DM.

Citing Articles

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PMID: 39860464 PMC: 11766419. DOI: 10.3390/jcm14020458.

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